基于灰关联度的锂电池组SOH评价方法研究  

Lithium-ion battary pack SOH evaluate method based on gray correlation degree

作　　者：尚丽平[1] 王顺利[1] 李占锋[2] 马有良[2] 夏承成 

机构地区：[1]西南科技大学信息工程学院,四川绵阳621010 [2]西南科技大学制造科学与工程学院,四川绵阳621010

出　　处：《电源技术》2015年第11期2381-2383,2418,共4页Chinese Journal of Power Sources

基　　金：国家自然科学基金(11176032);四川省科技支撑计划(2014GZ0078)

摘　　要：为进一步提高锂离子蓄电池组健康状态评价准确性,为蓄电池组维护人员日常维护提供依据,保证其在飞机应急供电等应用中的安全性,针对锂离子蓄电池组健康状态评价问题,基于灰关联度加权综合评价思想,提出了基于灰关联度的蓄电池SOH评价方法,研究了灰关联建模方法及SOH等级综合评价过程。实验结果表明,提出的SOH综合评价模型能够有效预测蓄电池健康状态,对锂离子蓄电池组SOH预测等级判断准确率达到98%,提高了SOH预测的可靠性与时效程度,实现了锂离子蓄电池组健康状态有效评估。An battery SOH correlation evaluation method based on weighted gray correlation degree comprehensive evaluation thought was presented. In order to further improve the lithium-ion battery health status evaluate accuracy, a basis for personnel daily maintenance of the battery pack is provided to ensure its security such as aircraft emergency power applications and so on. The lithium-ion batteries health status was evaluated, studying the gray relational modeling methods and SOH grade comprehensive evaluation process. Experimental results show that the proposed SOH comprehensive evaluation model can effectively predict the battery health status, and the lithium-ion battery SOH predict judgment accurately reaches the level of 98%, and the reliability and timeliness of SOH forecasts extent are increased, also the lithium-ion battery pack health status effective assessment is achieved.

关 键 词：锂电池组 SOH 灰关联度 综合评价 相关反馈 

分 类 号：TM912.9[电气工程—电力电子与电力传动]